Learning, Inference & Memory

Research

Finding and exploiting patterns and regularities in the environment is a critical brain function for animals living in a complex yet structured world. Individuals can deduce abstract relations, and learn these regularities through experience, and use this prior information to guide future behaviour. The process of inferring statistical patterns and priors constitutes the foundation of further cognitive abilities. How do animals infer these patterns and relations, and how priors are formed, represented, and stored?

Our past, present, and future are intimately linked by our memories of various timescales. The brain is constantly engaged in storing new memories and executing actions while integrating incoming sensory input with past memories and internal models of the world. What are the fundamental principles of (sensory) memory organization, and their utilization in inference problems? How are learned priors integrated in memory, or used in combination with new sensory information?

At LIM Lab we employ a synergistic combination of theory and experiment to tackle the fundamental principles of neuronal computations underlying sensory memory organization and sensory inference. We use high-throughput training to combine sophisticated, well-controlled and quantifiable behavioral paradigms with powerful tools to monitor and manipulate neural circuits. In all of our research programs, experiments are intertwined with hypotheses drawn from theoretical investigations and computational models.